The impact of ventilation rate on reducing the microorganisms load in the air and on surfaces in a room‐sized chamber

Abstract Hospital‐acquired infections (HAIs) are a global challenge incurring mortalities and high treatment costs. The environment plays an important role in transmission due to contaminated air and surfaces. This includes microorganisms' deposition from the air onto surfaces. Quantifying the deposition rate of microorganisms enables understanding surface contamination and can inform strategies to mitigate the infection risk. We developed and validated a novel Automated Multiplate Passive Air Sampling (AMPAS) device. This enables sequences of passive deposition samples to be collected over a controlled time period without human intervention. AMPAS was used with air sampling to measure the effect of ventilation rate and spatial location on the deposition rate of aerosolized Staphylococcus aureus in a 32 m3 chamber. Increasing the ventilation rate from 3 to 6 ACH results in a reduction of microbial load in the air and on surfaces by 45% ± 10% and 44% ± 32%, respectively. The deposition rate onto internal surfaces λd was calculated as 1.38 ± 0.48 h−1. Samples of airborne and surface microorganisms taken closer to the ventilation supply showed a lower concentration than close to the extract. The findings support the importance of controlling the ventilation and the environmental parameters to mitigate both air and surface infection risks in the hospital environment.

The importance of managing surface contamination for reducing transmission of infection in hospitals has been a topic of considerable interest in recent years. Studies show that when the surface bioburden increases, so does the risk of HAIs. 3 Both hand contact and the deposition of microorganisms from the air can cause this surface contamination. The surface cleaning regime and hand hygiene compliance have been examined, and both were found to minimize surface contamination and consequently, infection risk. [4][5][6] A review by Otter et al. 7 indicated that there is growing evidence that contaminated surfaces are important for the transmission of several HAIs, including C. difficile, MRSA, A. baumannii, P. aeruginosa, and norovirus, and that outbreaks are better controlled when greater attention is paid to environmental decontamination. Dancer (2004) 8 suggested that quantitative measurement of surface bioburden in a hospital could be used as a hygiene standard to manage infection risk, with a proposed aerobic colony count of <5 cfu.cm −2 suggested as indicative of an appropriate level of cleanliness.
Although microorganisms deposited on surfaces are recognized as a route to contamination, the factors which influence deposition have not been thoroughly addressed, and there is currently a lack of evidence about the contribution that deposited microorganisms make to infection risk. For many diseases, it is difficult to assess the relative importance of direct airborne (inhalation) exposure compared with indirect surface transmission, yet the two are related, as it is evident that airborne microorganisms deposit onto surfaces.
Previous work shows that passive air sampling results can show the relation between air contamination and surface contamination and could thus possibly be used as a proxy for infection risk. 3 Pasquarella et al. (2000) 9 provide a detailed overview of active and passive air sampling and conclude that although passive samples cannot differentiate between different sizes of particles that deposit from the air, they can still provide a useful quantitative assessment of the microbial burden in the air as well as the contribution that microorganisms in air make to surface contamination. Although strategies such as improved ventilation and the addition of air cleaning devices have been found to affect the microbial bioburden in air 10 and to reduce airborne transmission, 2 there is limited evidence that these strategies can also decrease the hazard of transmission through surfaces.
To evaluate the relationships between the bioburden in air and deposition onto surfaces, it is necessary to undertake active and passive air sampling simultaneously, which can allow the calculation of deposition rates. Previous work has reported a 0.10-0.80 (ℎ −1 ) loss rate due to the deposition of dry (non-biological) particles 0.55-1.91 μm in diameter onto surfaces at varying fan speeds (0, 5.4, 14.2, and 19.1 cm.s −1 ) in a laboratory room of 14.2 m 3 volume. 11 Another study that was conducted in a Class II biological safety cabinet of size 0.07 m 3 and nebulized Staphylococcus aureus (S. aureus), has considered varying ventilation rates and sampling locations and found that the loss rate due to deposition of S. aureus onto surfaces is 0.14 h −1 at a ventilation rate of 1.7-18 ACH. 12 Previous studies have also used passive sampling to measure the spatial variation in the deposition under a few different room geometries in comparison with a computational fluid dynamics (CFD) model using S. aureus in a biological chamber of size 32 m 3 . 13 In the hospital, Wong et al. 14 performed active and passive sampling at the same time and found that the loss rate due to deposition of the total aerobic count was 2.77 h −1 in the microbiological office and 5.5 h −1 in the intensive care unit.
The passive sampling technique is essential in this research; however, it provides an aggregate sample over a period of time. The variation of deposition rate with time in these previous chamber studies was not investigated due to the lack of a device to collect the microorganisms at intervals of time during the whole experiment. For this reason, the results could not show the full time-cycle curve leading to a certain concentration or measure variability during steady-state conditions. This is expected because it is difficult to capture the transient effects without employing an automated method. According to our knowledge, there is no commercial equipment that can expose the settle plates to the air for a defined period before covering them.
In this study, we propose and test a new approach, the Automated Multiplate Passive Air Sampler (AMPAS), for remotely measuring microbial deposition over time. The contributions of this paper include (i) developing and testing a novel configurable device that can expose a settle plate to air for a pre-determined interval, cover it, and autonomously expose a different one and (ii) investigating the effect of ventilation and spatial location on the deposition rate of microorganisms on surfaces in a controlled mechanically ventilated chamber setting. rotating tray controlled by a stepper motor ( Figure 1). The device is programmed to expose each agar plate to the microorganisms in the air at pre-determined times and for pre-programmed periods before covering them, without human intervention, to ensure they are no longer exposed to air.
The main electronic and mechanical components of the device are the microcontroller, stepper motor, motor driver module, power source, box container, and circular trays. The microcontroller (Elegoo mega 2560) was controlled by a C program to manage the opera- The timing of AMPAS air exposure was tested using a stopwatch for periods of 10, 60, 600, and 3600 s. The timing was accurate in all cases since it was controlled by a C-function that provides timing accuracy to the millisecond.

| Microbial experiments
The microbial experiments were all conducted in the controlled aerobiological chamber ~32 m 3 (Figure 2) with the same ventilation regime (high grid inlet-low grid outlet) as in Eadie et al. 15  An initial pilot study found that there is 7% ± 2% of natural decay of S. aureus in the same environment and experiment time. The chamber was set at an ambient air temperature of 24 ± 1 °C, with a relative humidity of 50% ± 2%. F I G U R E 1 Automated multiplate passive air sampling device and components.

| Checking the negative control of AMPAS
In the design of AMPAS, it is assumed that when the test plate is ex-

F I G U R E 4
Sampling results from the negative control experiment before making improvements to the device. exposed to air, and plates 2-6 were covered throughout the experiment. A continuous release of aerosolized S. aureus was introduced to the chamber for 165 min at 6 ACH. The experiment was replicated three times.
The initial experiment (see results Figure 4) showed that during this controlled study, there was contamination on plates 2-6. To For AMPAS, plate number 1 was excluded because it included the build-up and decay states rather than the steady state alone, and in each experiment, the results from all four AMPAS devices exposed in the same time interval were collated and presented as a single value to increase the surface area of sampling.
Ventilation and nebulization commenced at the start of each experiment, and the first 60 min were employed to let the room achieve steady-state conditions. Air and surface sampling then lasted 75 min with the nebulizer and ventilation operating continuously. Following sampling, the nebulizer was switched off, and the room ventilation rate was increased to 12 ACH for 30 min to flush any remaining airborne microorganisms from the room. Following the experiment, the plates were incubated at 37°C for 24 h. A correction table (appendix B-400 Hole Count) was used to apply positive hole correction for the air samples to correct for potential over-counting under higher bioaerosol concentrations. 16 The percentage of bioaerosols load reduction and deposition microorganism rate through the effect of changing ventilation from 3 to 6 ACH was calculated using Equation 1 Where, R l is the percentage of reduction in a specific location (inlet or outlet), i is the number of samples of data, m 3,l is the mean of bioaerosols load or deposited microorganism load in a specific location (inlet or outlet) at 3ACH, n i,6,l is the single data value at the same location l for sample i at 6ACH. For example, at the inlet location (L) for bioaerosols load, i equals to 30, m 3,l equals to 3797 cfu.m −3 , n i,6,l equals to is an array of 30 values (n 1,6,l , n 2,6,l … . n i,6,l ).

| Statistical analysis
R version 4.2.0 was used to process data and plot the graphs. 17 A one-way analysis of variance test was conducted to evaluate the separate hypotheses that no difference existed between sampling location or device design. A significance level of 0.05 was used throughout.

| The negative control of AMPAS
The initial experiment showed that although plate 1 (the test plate) generally had higher deposition, all plates had similar concentrations of S. aureus, indicating that the microorganisms from the air are depositing on the plates even when they are assumed to be protected ( Figure 4). This shows that deposition is complicated, with air movement through the sampler device enabling deposition onto plates that were not open vertically to the air. As well as demonstrating that the device required modification it also illustrates that microbial contamination of surfaces that do not appear to be directly exposed can happen with low velocity airflows created only by a ventilation system; this may have implications for contamination of other complex devices in clinical settings.

| The final AMPAS design
The use of plastic wrap around the perimeter of the AMPAS device (A and B) had the most significant effect and, together with reducing the gap to 1 mm (A) significantly (p < 0.0001), improved the reliability of the collected data and eliminated the problem of undesired contamination ( Figure 5).

| Checking the consistency of deposition rate onto the plates of AMPAS
The average deposited microorganisms on plates 2-6 showed no significant difference while plate number (1) had a higher deposition, due to being exposed to air for a more extended period at the beginning and the end of the experiment Figure 6.
As shown in Figure 7, different devices with the same design and settings had no significant difference in the deposition of microorganisms. This confirms that using the AMPAS device provides consistent results over time under steady-state conditions, and that there is no significant difference (p > 0.5) between the four devices used in the study.  Where, y is the concentration of microorganisms on surface (cfu.m −2 .h −1 ) and x is bioaerosols load (cfu.m −3 ). This equation (2) is only accurate when there is a high concentration of bioaerosols and in a controlled environment.

| The loss rate due to deposition onto surfaces
Under the steady-state conditions, the total loss rate due to deposition onto surfaces can be calculated as in Equation 3 where, d is the loss rate due to deposition onto total inner room sur- Where C sf is the indoor deposited microorganisms' concentration on (2) y = 0.22x + 2575 Comparison of the deposited microorganisms on six plates.

F I G U R E 7
Comparison of the deposited microorganisms on four AMPAS devices (1 mm gap with plastic wrap) under steady state conditions.
The deposition rate of bioaerosols on the ceiling and walls was substituted by a percentage equal to 23% and 44% of the deposited microorganisms' concentration on the floor, respectively, based on Liu et al. 18 Although this is an estimation and it allows for biased results because the inlet and outlet for ventilation for Liu et al. 18 were located in the ceiling, which may change the surface deposition pattern. Assuming that the floor and the ceiling have the same surface area, Equation 5 uses the same principle as Equation 3 and calculates the loss rate due to deposition, taking into account the deposition onto the walls and ceiling as a percentage of the deposition on the floor (based on real data from the experiment).

F I G U R E 9
The mean deposited microorganisms load under the steadystate conditions at 3 and 6 ACH ventilation rates sampled near the ventilation inlet and the outlet.
Where, w and c are the percentages of C sf , which is the indoor deposited microorganisms' concentration on the floor (cfu. m −2 . h −1 ) for deposition on the walls and ceiling, respectively. The total loss rate due to deposition on surfaces ( d,f ) was 0.6 ± 0.33 (h −1 ) ( Figure 11) and all surfaces d was 1.38 ± 0.48 (h −1 ).

| DISCUSS ION
To the best of our knowledge, this is the first study to investigate the impact of ventilation rate on the deposition rate of microorganisms onto surfaces over time, using a novel passive sampling device in a room-scale controlled environment under steady-state conditions.
The validation of AMPAS showed that bacteria were able to enter through the 5 mm gap in the initial design and contaminate agar The results show that increasing the ventilation rate from 3 ACH to 6 ACH results in a reduction of bioaerosols load in the air by 43% ± 8% and 45% ± 10% when sampling near the inlet and the outlet, respectively. This result is close to the 50% reduction expected through the well-mixed assumption that is typically used to estimate the impact of ventilation rate on contaminants in air. The mean reduction in our experiments is consistently slightly lower than 50% which may be due to the effects of air mixing patterns, sampling effects or that in the real-world setting it is not possible to measure the ventilation rate to the same accuracy as a theoretical model.
The same trend was seen in the deposited data, with an increase in the ventilation rate reducing the deposited microorganism load by 33% ± 25% and 44% ± 32% when sampled near the inlet and the outlet, respectively. These values are a similar order of magnitude reduction with the increase in ventilation rate as seen in the air samples suggesting that the relative deposition rate remains fairly consistent with a change in ventilation rate under the conditions studied. The results show that there does appear to be more variability in the surface sample data than the air sample data. In the real world, the loss rate due to deposition onto the floor surface has been found to be 5-10 times higher than in our experiments; it was 2.77 h −1 in the microbiological office and 5.5 h −1 in the ICU. 14 The real-world environments and especially hospital environments, usually face a complexity of interactions between several environmental and behavioral factors, 19  project (EP/P023312/1) and EPSRC DTP studentship project (1955605).

CO N FLI C T O F I NTE R E S T
None to declare.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are openly available in github at https://github.com/Wasee mhiwa r/AMPAS -and-Venti latio n-paper.git.